Engineered bacteria launch and control an oncolytic virus.

The ability of bacteria and viruses to selectively replicate in tumors has led to synthetic engineering of new microbial therapies. Here we design a cooperative strategy whereby S. typhimurium bacteria transcribe and deliver the Senecavirus A RNA genome inside host cells, launching a potent oncolytic viral infection. Then, we engineer the virus to require a bacterially delivered protease in order to achieve virion maturation, demonstrating bacterial control over the virus. This work extends bacterially delivered therapeutics to viral genomes, and the governing of a viral population through engineered microbial interactions. One-Sentence Summary: Bacteria are engineered to act as a synthetic "capsid" delivering Senecavirus A genome and controlling its spread.

Segmentation with Residual Attention U-Net and an Edge-Enhancement Approach Preserves Cell Shape Features.

The ability to extrapolate gene expression dynamics in living single cells requires robust cell segmentation, and one of the challenges is the amorphous or irregularly shaped cell boundaries. To address this issue, we modified the U-Net architecture to segment cells in fluorescence widefield microscopy images and quantitatively evaluated its performance. We also proposed a novel loss function approach that emphasizes the segmentation accuracy on cell boundaries and encourages shape feature preservation. With a 97% sensitivity, 93% specificity, 91% Jaccard similarity, and 95% Dice coefficient, our proposed method called Residual Attention U-Net with edge-enhancement surpassed the state-of-the-art U-Net in segmentation performance as evaluated by the traditional metrics. More remarkably, the same proposed candidate also performed the best in terms of the preservation of valuable shape features, namely area, eccentricity, major axis length, solidity and orientation. These improvements on shape feature preservation can serve as useful assets for downstream cell tracking and quantification of changes in cell statistics or features over time.

Sindbis Macrodomain Poly-ADP-Ribose Hydrolase Activity Is Important for Viral RNA Synthesis.

ADP-ribosylation is a highly dynamic posttranslational modification frequently studied in stress response pathways with recent attention given to its role in response to viral infection. Notably, the alphaviruses encode catalytically active macrodomains capable of ADP-ribosylhydrolase (ARH) activities, implying a role in remodeling the cellular ADP-ribosylome. This report decouples mono- and poly-ARH contributions to macrodomain function using a newly engineered Sindbis virus (SINV) mutant with attenuated poly-ARH activity. Our findings indicate that viral poly-ARH activity is uniquely required for high titer replication in mammalian systems. Despite translating incoming genomic RNA as efficiently as WT virus, mutant viruses have a reduced capacity to establish productive infection, offering a more complete understanding of the kinetics and role of the alphavirus macrodomain with important implications for broader ADP-ribosyltransferase biology. IMPORTANCE Viral macrodomains have drawn attention in recent years due to their high degree of conservation in several virus families (e.g., coronaviruses and alphaviruses) and their potential druggability. These domains erase mono- or poly-ADP-ribose, posttranslational modifications written by host poly-ADP-ribose polymerase (PARP) proteins, from undetermined host or viral proteins to enhance replication. Prior work determined that efficient alphavirus replication requires catalytically active macrodomains; however, which form of the modification requires removal and from which protein(s) had not been determined. Here, we present evidence for the specific requirement of poly-ARH activity to ensure efficient productive infection and virus replication.

Quantitative measurements of early alphaviral replication dynamics in single cells reveals the basis for superinfection exclusion.

While decades of research have elucidated many steps of the alphavirus lifecycle, the earliest replication dynamics have remained unclear. This missing time window has obscured early replicase strand-synthesis behavior and prevented elucidation of how the first events of infection might influence subsequent viral competition. Using quantitative live-cell and single-molecule imaging, we observed the initial replicase activity and its strand preferences in situ and measured the trajectory of replication over time. Under this quantitative framework, we investigated viral competition, where one alphavirus is able to exclude superinfection by a second homologous virus. We show that this appears as an indirect phenotypic consequence of a bidirectional competition between the two species, coupled with the rapid onset of viral replication and a limited total cellular carrying capacity. Together, these results emphasize the utility of analyzing viral kinetics within single cells.

Rapid screening of engineered microbial therapies in a 3D multicellular model.

Synthetic biology is transforming therapeutic paradigms by engineering living cells and microbes to intelligently sense and respond to diseases including inflammation, infections, metabolic disorders, and cancer. However, the ability to rapidly engineer new therapies far outpaces the throughput of animal-based testing regimes, creating a major bottleneck for clinical translation. In vitro approaches to address this challenge have been limited in scalability and broad applicability. Here, we present a bacteria-in-spheroid coculture (BSCC) platform that simultaneously tests host species, therapeutic payloads, and synthetic gene circuits of engineered bacteria within multicellular spheroids over a timescale of weeks. Long-term monitoring of bacterial dynamics and disease progression enables quantitative comparison of critical therapeutic parameters such as efficacy and biocontainment. Specifically, we screen Salmonella typhimurium strains expressing and delivering a library of antitumor therapeutic molecules via several synthetic gene circuits. We identify candidates exhibiting significant tumor reduction and demonstrate high similarity in their efficacies, using a syngeneic mouse model. Last, we show that our platform can be expanded to dynamically profile diverse microbial species including Listeria monocytogenes, Proteus mirabilis, and Escherichia coli in various host cell types. This high-throughput framework may serve to accelerate synthetic biology for clinical applications and for understanding the host-microbe interactions in disease sites.

Synthetic recording and in situ readout of lineage information in single cells.

Reconstructing the lineage relationships and dynamic event histories of individual cells within their native spatial context is a long-standing challenge in biology. Many biological processes of interest occur in optically opaque or physically inaccessible contexts, necessitating approaches other than direct imaging. Here we describe a synthetic system that enables cells to record lineage information and event histories in the genome in a format that can be subsequently read out of single cells in situ. This system, termed memory by engineered mutagenesis with optical in situ readout (MEMOIR), is based on a set of barcoded recording elements termed scratchpads. The state of a given scratchpad can be irreversibly altered by CRISPR/Cas9-based targeted mutagenesis, and later read out in single cells through multiplexed single-molecule RNA fluorescence hybridization (smFISH). Using MEMOIR as a proof of principle, we engineered mouse embryonic stem cells to contain multiple scratchpads and other recording components. In these cells, scratchpads were altered in a progressive and stochastic fashion as the cells proliferated. Analysis of the final states of scratchpads in single cells in situ enabled reconstruction of lineage information from cell colonies. Combining analysis of endogenous gene expression with lineage reconstruction in the same cells further allowed inference of the dynamic rates at which embryonic stem cells switch between two gene expression states. Finally, using simulations, we show how parallel MEMOIR systems operating in the same cell could enable recording and readout of dynamic cellular event histories. MEMOIR thus provides a versatile platform for information recording and in situ, single-cell readout across diverse biological systems.

Inferring Cell-State Transition Dynamics from Lineage Trees and Endpoint Single-Cell Measurements.

As they proliferate, living cells undergo transitions between specific molecularly and developmentally distinct states. Despite the functional centrality of these transitions in multicellular organisms, it has remained challenging to determine which transitions occur and at what rates without perturbations and cell engineering. Here, we introduce kin correlation analysis (KCA) and show that quantitative cell-state transition dynamics can be inferred, without direct observation, from the clustering of cell states on pedigrees (lineage trees). Combining KCA with pedigrees obtained from time-lapse imaging and endpoint single-molecule RNA-fluorescence in situ hybridization (RNA-FISH) measurements of gene expression, we determined the cell-state transition network of mouse embryonic stem (ES) cells. This analysis revealed that mouse ES cells exhibit stochastic and reversible transitions along a linear chain of states ranging from 2C-like to epiblast-like. Our approach is broadly applicable and may be applied to systems with irreversible transitions and non-stationary dynamics, such as in cancer and development.

Spatial Control of Bacteria Using Screen Printing.

Synthetic biology has led to advances in both our understanding and engineering of genetic circuits that affect spatial and temporal behaviors in living cells. A growing array of native and synthetic circuits such as oscillators, pattern generators, and cell-cell communication systems has been studied, which exhibit spatiotemporal properties. To better understand the design principles of these genetic circuits, there is a need for versatile and precise methods for patterning cell populations in various configurations. In this study, we develop a screen printing methodology to pattern bacteria on agar, glass, and paper surfaces. Initially, we tested three biocompatible resuspension media with appropriate rheological properties for screen printing. Using microscopy, we characterized the resolution and bleed of bacteria screen prints on agar and glass surfaces, obtaining resolutions as low as 188 µm. Next, we engineered bacterial strains producing visible chromoproteins analogous to the cyan, magenta, and yellow subtractive color system for the creation of multicolored bacteria images. Using this system, we printed distinct populations in overlapping or interlocking designs on both paper and agar substrates. These proof-of-principle experiments demonstrated how the screen printing method could be used to study microbial community interactions and pattern formation of biofilms at submillimeter length scales. Overall, our approach allows for rapid and precise prototyping of patterned bacteria species that will be useful in the understanding and engineering of spatiotemporal behaviors in microbial communities.

Single-cell transcriptome analysis reveals dynamic changes in lncRNA expression during reprogramming.

Cellular reprogramming highlights the epigenetic plasticity of the somatic cell state. Long noncoding RNAs (lncRNAs) have emerging roles in epigenetic regulation, but their potential functions in reprogramming cell fate have been largely unexplored. We used single-cell RNA sequencing to characterize the expression patterns of over 16,000 genes, including 437 lncRNAs, during defined stages of reprogramming to pluripotency. Self-organizing maps (SOMs) were used as an intuitive way to structure and interrogate transcriptome data at the single-cell level. Early molecular events during reprogramming involved the activation of Ras signaling pathways, along with hundreds of lncRNAs. Loss-of-function studies showed that activated lncRNAs can repress lineage-specific genes, while lncRNAs activated in multiple reprogramming cell types can regulate metabolic gene expression. Our findings demonstrate that reprogramming cells activate defined sets of functionally relevant lncRNAs and provide a resource to further investigate how dynamic changes in the transcriptome reprogram cell state.

Dynamic heterogeneity and DNA methylation in embryonic stem cells.

Cell populations can be strikingly heterogeneous, composed of multiple cellular states, each exhibiting stochastic noise in its gene expression. A major challenge is to disentangle these two types of variability and to understand the dynamic processes and mechanisms that control them. Embryonic stem cells (ESCs) provide an ideal model system to address this issue because they exhibit heterogeneous and dynamic expression of functionally important regulatory factors. We analyzed gene expression in individual ESCs using single-molecule RNA-FISH and quantitative time-lapse movies. These data discriminated stochastic switching between two coherent (correlated) gene expression states and burst-like transcriptional noise. We further showed that the "2i" signaling pathway inhibitors modulate both types of variation. Finally, we found that DNA methylation plays a key role in maintaining these metastable states. Together, these results show how ESC gene expression states and dynamics arise from a combination of intrinsic noise, coherent cellular states, and epigenetic regulation.